docstr: Normalize the array to have unit L1 norm.
  
  Parameters
  ----------
  self
      Input array.
  axis
      Axis or axes along which to normalize. If ``None``,
      the whole array is normalized.
  out
      Optional output array, for writing the result to.
      It must have a shape that the inputs broadcast to.
  
  Returns
  -------
  ret
      The normalized array.
  
  Examples
  --------
  >>> x = ivy.array([[1., 2.], [3., 4.]])
  >>> y = x.l1_normalize(axis=1)
  >>> print(y)
  ivy.array([[0.33333334, 1.33333337],
         [1.28571439, 2.28571439]])
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code: def l1_normalize(
      self: ivy.Array,
      axis: Optional[Union[int, Tuple[int, ...]]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """Normalize the array to have unit L1 norm.
  
      Parameters
      ----------
      self
          Input array.
      axis
          Axis or axes along which to normalize. If ``None``,
          the whole array is normalized.
      out
          Optional output array, for writing the result to.
          It must have a shape that the inputs broadcast to.
  
      Returns
      -------
      ret
          The normalized array.
  
      Examples
      --------
      >>> x = ivy.array([[1., 2.], [3., 4.]])
      >>> y = x.l1_normalize(axis=1)
      >>> print(y)
      ivy.array([[0.33333334, 1.33333337],
             [1.28571439, 2.28571439]])
      """
      return ivy.l1_normalize(self, axis=axis, out=out)
  
file_path: ivy/ivy/data_classes/array/experimental/norms.py
imports: import abc
  from typing import Optional, Union, Tuple
  import ivy
label_desc: Use image node_id 1 for calling the _ArrayWithNormsExperimental obj's underlying member method code with example usage: obj.l1_normalize(axis, out) and returns: ivy